Traditionally, electrical brain-computer interfaces (BCIs) have required the assembly of two separate components: electrodes for interfacing with tissue and electronics for signal acquisition and stimulation. Furthermore, these electronics required cabled connections to workstations for data processing and control. Efforts to overcome these limitations have made significant progress in the last decade. Now, there are in vivo validated monolithic electrophysiological BCI devices, exemplified by the Neuropixels, that integrate the two components onto a single platform. At the same time, a new generation of fully wireless BCI devices that reside entirely under the skin has been developed. Despite these advancements, the current state-of-the-art BCIs have yet to overcome both challenges simultaneously. Multi-channel, high-bandwidth monolithic BCIs still require percutaneous wired connections, whereas wireless BCIs rely on the assembly of discrete components that result in bulky form factors. The next generation of BCIs calls for a new paradigm that integrates electrodes and electronics into a miniaturized form factor while supporting a fully wireless operation. This thesis contributes to the collaborative effort that presents such a paradigm through the development of a wireless, battery-free micro-electrocorticography (μECoG) device that monolithically integrates electrodes, signal processing, data telemetry, and powering onto a single complementary metal-oxide-semiconductor (CMOS) substrate. The device contains 65,536 recording and 16,384 stimulation channels, from which a programmable subset of up to 1024 channels can berecorded at a given time. Implemented in a mechanically flexible, 50-μm-thick form factor with a total volume of only 7.2 mm³, the device is implanted entirely in the subdural space and conforms to the contour of the cortical tissue surface. A custom "relay station" provides wireless powering and bi-directional communication to the implant from outside the body. The system was validated through a series of proof-of-concept in vivo recordings from different cortical regions of a pig and non-human primates, reliably decoding brain signals at high spatiotemporal resolution. By using a unique, fully integrated architecture, the BCI developed in this work achieves orders-of-magnitude improvements in volumetric efficiency and channel count over existing approaches, setting a milestone for the next generation of BCI devices.

The advent of the Personal Computer into the technical world has, at an extremely reasonable expense and trouble, made available to us, considerable computational power. But, as it was with computers, the next logical step is to have multiple units running in concert, or, in other words, sharing the load. This leads to the concept of Multiprocessing in order to attain an enhancement in operation speed and superior efficiency. The IBM PC is a versatile and market proven personal computer with a very large volume of software support and the STD Bus is a standard that has been developed to cope with a variable support, i.e. different processors and different I/O capabilities. Together, they combine the user interface - the display and keyboard · of the PC, the processing capabilities of the PC, the I/O capabilities of the STD Bus and the support processing possible on the STD Bus. The resulting system is powerful, easy to use and it has a lot of scope for development. / Master of Science

A major design aspect of touch tablet operation is the display/control (D/C) gain. The primary objective of this research was the development and optimization of a variable D/C gain to improve human performance with touch tablets. This variable gain minimizes the speed-accuracy trade-off problem associated with traditional D/C gains. An additional objective.of this research was to determine the effect of tablet size on human performance. Display/control (D/C) gain is defined as the amount of movement which occurs on the display in response to a unit amount of movement of the control. With traditional D/C gains, there is a trade-off between low D/C gain which enables fine positioning, but results in very slow cursor movement, and high D/C gain which produces quick cursor movement but results in poor fine positioning ability. A lead-lag compensator which ameliorates this trade-off problem was developed. A lead-lag compensator is composed of a pure position gain component plus an additional velocity gain component. The results indicate that a lead-lag compensator greatly increased the target acquisition rate relative to a traditional D/C gain system. Percentage error increased with lead-lag compensation relative to an uncompensated system. The overall error rates were very low in all cases, however. Tablet size did not appear to significantly affect performance; performance on the three tablet sizes was generally consistent. / M.S.

M. S.

In many applications the microprocessor can represent an attractive design alternative to hardwired integrated circuitry. Such designs can offer substantial in teras of flexibility, cost and reliability, generally at the expense of operating speed. This paper contains a detailed description of such a system, in which a Zilog Z80 microprocessor is used as the basis for an intelligent controlling interface between an assortment of experimental instruments and a PDP-11 minicomputer. The details of the hardware and software designs, which could be employed in a wide range of experiment and process control applications, are presented. / M. S.

Developments in materials science and engineering have significantly enhanced the recording and stimulation capabilities of electrophysiological neural interface devices. Enhanced biocompatibility has increased the viability and longevity of such systems, with particularly interesting advances resulting from the utilization of organic and mixed-conductive conjugated polymers. These materials tend to improve biocompatibility and signal quality by overcoming material limitations of conventional metallic electrodes. Simultaneously, advanced microfabrication methods have increased the spatiotemporal resolution and signal quality of recorded data without added invasiveness. The research work presented in this dissertation touches upon three aspects of relevance for improved neural interface use: i) improving the accuracy of histological verification procedures in research using naturally abundant organic materials; ii) introducing unconventional electrodes for neural recordings and localized drug delivery by utilizing conductive organic polymers and clinical supply items; iii) applying a high-density electrocorticography (ECoG) array to study differential neural oscillation patterns underlying memory processing in vivo. First, we showcase a chitosan (CS) based, solution-processable film for localizing neural implants by leveraging CSs intrinsic fluorescence, without impeding data quality or cell viability. Second, we develop a mixed-conductive suture by using standard silk sutures and the mixed-conductive polymer PEDOT:PSS. The resulting device (E-Suture) is shown to safely interface with live tissue and possess high-fidelity recording and stimulation capabilities as well as applicability for localized drug delivery thanks to the mixed-conductivity of PEDOT:PSS. Finally, we leverage high spatiotemporal resolution ECoG arrays to show that distinctive oscillatory memory biomarkers in the neocortex and hippocampus show significant but differential temporal coupling patterns in response to consolidation of new information and reconsolidation of that information at a later time in rats. This dissertation demonstrates the utility of different organic materials for the enhancement of neural interface functions at multiple phases of the device life cycle as well as a concrete demonstration of improved electrophysiological recording devices in answering key questions of foundational neuroscience.

The project, presented in this paper, developed a web-based tool that provides training and technical support in the use of computers to employees at the San Bernardino Community College District. The purpose of this project was with the lack of one support system it has become necessary to create one place for support entities to share their expertise with one another and with the campus community. This project creates a web presence that all of these groups can contribute to. This system starts out small and creates a skeletal system that will allow for continued development after the project is over.

Thesis (MEng)--Stellenbosch University, 2014. / ENGLISH ABSTRACT: Muscular dystrophy, spinal cord injury, or amyotrophic lateral sclerosis (ALS) are injuries and disorders that disrupts the neuromuscular channels of the human body thus prohibiting the brain from controlling the body. Brain computer interface (BCI) allows individuals to bypass the neuromuscular channels and interact with the environment using the brain. The system relies on the user manipulating his neural activity in order to control an external device. Electroencephalography (EEG) is a cheap, non-invasive, real time acquisition device used in BCI applications to record neural activity. However, noise, known as artifacts, can contaminate the recording, thus distorting the true neural activity. Eye blinks are a common source of artifacts present in EEG recordings. Due to its large amplitude it greatly distorts the EEG data making it difficult to interpret data for BCI applications. This study proposes a new combination of techniques to detect and correct eye blink artifacts to improve the quality of EEG for BCI applications. Independent component analysis (ICA) is used to separate the EEG signals into independent source components. The source component containing eye blink artifacts are corrected by detecting each eye blink within the source component and using a trained wavelet neural network (WNN) to correct only a segment of the source component containing the eye blink artifact. Afterwards, the EEG is reconstructed without distorting or removing the source component. The results show a 91.1% detection rate and a 97.9% correction rate for all detected eye blinks. Furthermore for channels located over the frontal lobe, eye blink artifacts are corrected preserving the neural activity. The novel combination overall reduces EEG information lost, when compared to existing literature, and is a step towards improving EEG pre-processing in order to provide cleaner EEG data for BCI applications. / AFRIKAANSE OPSOMMING: Spierdistrofie, ’n rugmurgbesering, of amiotrofiese laterale sklerose (ALS) is beserings en steurnisse wat die neuromuskulêre kanale van die menslike liggaam ontwrig en dus verhoed dat die brein die liggaam beheer. ’n Breinrekenaarkoppelvlak laat toe dat die neuromuskulêre kanale omlei word en op die omgewing reageer deur die brein. Die BCI-stelsel vertrou op die gebruiker wat sy eie senuwee-aktiwiteit manipuleer om sodoende ’n eksterne toestel te beheer. Elektro-enkefalografie (EEG) is ’n goedkoop, nie-indringende, intydse dataverkrygingstoestel wat gebruik word in BCI toepassings. Nie net senuwee aktiwiteit nie, maar ook geraas , bekend as artefakte word opgeneem, wat dus die ware senuwee aktiwiteit versteur. Oogknip artefakte is een van die algemene artefakte wat teenwoordig is in EEG opnames. Die groot omvang van hierdie artefakte verwring die EEG data wat dit moeilik maak om die data te ontleed vir BCI toepassings. Die studie stel ’n nuwe kombinasie tegnieke voor wat oogknip artefakte waarneem en regstel om sodoende die kwaliteit van ’n EEG vir BCI toepassings te verbeter. Onafhanklike onderdeel analise (Independent component analysis (ICA)) word gebruik om die EEG seine te skei na onafhanklike bron-komponente. Die bronkomponent wat oogknip artefakte bevat word reggestel binne die komponent en gebruik ’n ervare/geoefende golfsenuwee-netwerk om slegs ’n deel van die komponent wat die oogknip artefak bevat reg te stel. Daarna word die EEG hervorm sonder verwringing of om die bron-komponent te verwyder. Die resultate toon ’n 91.1% opsporingskoers en ’n 97.9% regstellingskoers vir alle waarneembare oogknippe. Oogknip artefakte in kanale op die voorste lob word reggestel en behou die senuwee aktiwiteit wat die oorhoofse EEG kwaliteit vir BCI toepassings verhoog.

We have designed a simulation that can be used to train police officers. Digital simulations are more cost-effective than a human role play. Use of force decisions are complex and made quickly, so there is a need for better training and innovative methods. Using this simulation, we are measuring the degree of presence that a human experience in a virtual environment. More presence implies better training. Participants are divided into two groups in which one group performs the experiment using a screen, keyboard, and mouse, and another uses virtual reality controls. In this experiment, we use subjective measurements and physiological measurements. We offer a questionnaire to participants before and after play. We also record the participants change in heart rate, skin conductivity and skin temperature using Empatica device. By comparing the data collected from both groups, we prove that people experience more presence in the virtual environment.

Context Free Design Grammar (CFDG) is a programming language for defining recursive structures that can be used to create art. I use CFDG as a design space for genetic programming, experimenting with various options for crossover, mutation, and fitness. In this exploratory work, multiple generations are manually assessed to determine the usefulness of the mutation strategies and fitness functions. I find that simple value mutation and fitness that alters general program structure is not enough to produce an increase of interesting images in CFDG. I discuss these findings as well as future avenues of inquiry for genetic programming in artistic domains.